{"title":"Applications of Proteomic Technologies to Toxicology","authors":"Yue Ge, M. Bruno, H. Foth","doi":"10.1002/9780470744307.GAT213","DOIUrl":"https://doi.org/10.1002/9780470744307.GAT213","url":null,"abstract":"Proteomics is the large-scale study of gene expression at the protein level. This cutting edge technology has been extensively applied to toxicology research recently. The up-to-date development of proteomics has presented the toxicology community with an unprecedented opportunity to reexamine conventional toxicological principles, methods and practices, and to transform this traditional subject into more informative and comprehensive science for a better understanding of the potential toxic mechanisms and/or modes of action, toxicity pathways, environmental biomarkers, and assessment of adverse human health risks. The application of proteomics and other OMICS technologies to toxicology has given rise to the new field of toxicology, systems toxicology. This book chapter provides an introduction to modern proteomic technologies and approaches, with particular reference to their applications to toxicology. Key proteomic technologies such as two-dimensional gel electrophoresis based and mass spectrometry-based proteomic methods and approaches are described. Examples of recent applications of these technologies and methodologies to mechanistic toxicology and applied toxicology such as chemical toxicity testing and screening, clinical toxicology, drug discovery, environmental toxicity, and toxicity biomarker are presented. The discussion includes a focus on challenges and future directions of toxicoproteomics and systems toxicology. \u0000 \u0000 \u0000Keywords: \u0000 \u0000proteomics; \u0000toxicology; \u0000toxicity pathways; \u0000protein expression; \u0000protein post-translational modification; \u0000protein biomarker; \u0000systems toxicology","PeriodicalId":325382,"journal":{"name":"General, Applied and Systems Toxicology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2011-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126973577","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Application of Quantitative Proteomic Approaches to Toxicology","authors":"T. Prasad, R. Chaerkady","doi":"10.1002/9780470744307.GAT214","DOIUrl":"https://doi.org/10.1002/9780470744307.GAT214","url":null,"abstract":"Epidemiological and genetic studies have significantly contributed to our understanding of hazardous effects of various environmental pollutants on biological systems at a molecular level. However, only limited reports exist those describe proteomic alterations associated with toxicity of such pollutants. Proteomic signatures can be employed as biomarkers for exposure as well as toxicity. Improved protein/peptide labeling technologies have led to the development of a variety of methodologies for quantitative proteomics that can be used to obtain differential protein profiles. This review highlights various quantitative proteomic technologies, which can be applied to unravel proteomic changes in response to toxicants. \u0000 \u0000 \u0000Keywords: \u0000 \u0000biomarkers; \u0000clinical proteomics; \u0000iTRAQ; \u0000Arsenic; \u0000mass spectrometry; \u0000signaling pathways","PeriodicalId":325382,"journal":{"name":"General, Applied and Systems Toxicology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2011-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128921023","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Integration of Systems Toxicology into Drug Discovery","authors":"M. Fielden","doi":"10.1002/9780470744307.GAT210","DOIUrl":"https://doi.org/10.1002/9780470744307.GAT210","url":null,"abstract":"Success in the pharmaceutical industry is plagued by high rates of late-stage attrition because of unanticipated pre-clinical and clinical toxicity. In order to improve success rates, it is necessary to consider potential on- and off-target-mediated toxicity at an earlier stage in product development to shift attrition upstream in the process. This will help to avoid resource-intensive development activities, such as pre-clinical toxicology and human clinical studies, on compounds that are ultimately destined to fail. Large-scale gene expression profiling technologies, such as toxicogenomics, have the potential to diagnose and predict certain safety liabilities using in vitro and in vivo models. When used appropriately in the early stages of lead optimization and pre-clinical drug testing, it has the potential to improve compound selection at an earlier stage of drug discovery and thus decrease the probability of late-stage attrition. A more thorough understanding of a drug's mechanism of action and toxicity is also expected to improve human risk assessment and help define appropriate screening strategies to avoid toxicophores in subsequent iterations of drug discovery. This chapter will focus on the application of systems toxicology using toxicogenomics in drug discovery for the early safety assessment of small molecule therapeutics. \u0000 \u0000 \u0000Keywords: \u0000 \u0000discovery toxicology; \u0000drug discovery; \u0000in vitro; \u0000in vivo; \u0000lead optimization; \u0000microarray; \u0000toxicity prediction; \u0000toxicogenomics","PeriodicalId":325382,"journal":{"name":"General, Applied and Systems Toxicology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2011-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129056161","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"The Role of Oxidative Stress in Nanotoxicology","authors":"C. Sayes, N. Banerjee, A. Romoser","doi":"10.1002/9780470744307.GAT245","DOIUrl":"https://doi.org/10.1002/9780470744307.GAT245","url":null,"abstract":"The application of systems biology approaches is gaining popularity in the nanoparticle toxicology research (Brandenberger, 2010; Oberdorster, Oberdorster and Oberdorster, 2005; Nyland and Silbergeld, 2009). Over the past few years, there has been a movement toward describing and characterizing trends in nanotoxicological data sets. In order to interpret these observed trends, the use of a holistic perspective may be appropriate. One of the cornerstones of systems biology is the use of experimental and computational models. Nanotoxicology could benefit from these efforts. Both systems biology and nanotoxicology attempt to discover emergent properties of a system and link those properties, using a variety of techniques to environmental and human health. \u0000 \u0000 \u0000 \u0000While the investigations in the field of systems biology are frequently large in scale, nanotoxicology has yet to accomplish this feat, to date. Both fields require an interdisciplinary approach from experimentalists (biologist, chemists, toxicologists, and risk assessors) and quantitative scientists (biostatisticians, mathematicians, computer scientists, and engineers). Together, their efforts can be coordinated to improve the quality of science and to create, refine, and retest the experimental and computational models to accurately reflect, and eventually predict, biological, and toxicological observations. \u0000 \u0000 \u0000Keywords: \u0000 \u0000nanoparticles; \u0000oxidative stress; \u0000cellular uptake; \u0000reactive oxygen species (ROS); \u0000fluorescent probes; \u0000confocal microscopy; \u0000redox states; \u0000antioxidants","PeriodicalId":325382,"journal":{"name":"General, Applied and Systems Toxicology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2011-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122999381","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Role of the Endocannabinoid System in Systems Toxicity","authors":"C. Pistos, S. Theocharis","doi":"10.1002/9780470744307.GAT206","DOIUrl":"https://doi.org/10.1002/9780470744307.GAT206","url":null,"abstract":"The scientific knowledge regarding the modulation of the endogenous cannabinoid system and its effect on disease pathophysiology has been significantly improved in the last 20 years. Alterations in the expression of cannabinoid receptors, their main endogenous ligands (arachidonoylethanolamide and 2-arachidonoylglycerol), and related enzyme levels have been reported in different disease states, suggesting their important regulatory role. The pharmacological effects of synthetic compounds that selectively target the endocannabinoid system, established cause-effect relationships between endocannabinoids and the progress of several disorders. In this review, the importance of endocannabinoid system modulation and also the aspects of the underlying pathways leading to disease or target organ toxicity are reported. \u0000 \u0000 \u0000Keywords: \u0000 \u0000endocannabinoids; \u0000anandamide; \u00002-arachidoylglycerol; \u0000system toxicity; \u0000cannabinoid receptors; \u0000immune system; \u0000inflammation; \u0000fibrosis; \u0000I/R","PeriodicalId":325382,"journal":{"name":"General, Applied and Systems Toxicology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2011-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131511745","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"In Vivo Toxicity Studies of Metal and Metal Oxide Nanoparticles","authors":"A. Adamcakova-Dodd, P. Thorne, V. Grassian","doi":"10.1002/9780470744307.GAT244","DOIUrl":"https://doi.org/10.1002/9780470744307.GAT244","url":null,"abstract":"Manufactured nanomaterials are in more than 1000 consumer products that contain some nanotechnology-based material on the market today. In the last five years there has been much effort put toward understanding the health effects associated with nanoparticle exposure. Toxicity assessment plays a significant role in this effort since human exposure can occur during production processes, handling, as well as their use and application. Although, though there is a large body of literature on “ultrafine particles” from a pulmonary exposure assessment, one should proceed with caution to expand this information to nanomaterials as we are still just at the beginning stages of their toxicity assessment. In this chapter, we consider the respiratory system as the main route of exposure to nanoparticles and we focus our attention mainly on metal-based nanomaterials and in vivo models used to evaluate them. We also discuss available data for other materials, since similar material properties whether size, shape, or chemical composition could lead to comparable toxicities and this will help in the development of screening strategies for nanomaterials that are very much warranted at this time. \u0000 \u0000 \u0000Keywords: \u0000 \u0000metal nanoparticles; \u0000metal oxide nanoparticles toxicity; \u0000inhalation; \u0000instillation; \u0000mouse model; \u0000sub-acute exposure","PeriodicalId":325382,"journal":{"name":"General, Applied and Systems Toxicology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2011-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128750490","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Systems Biology: Integrating ‘‐Omics'‐Oriented Approaches to Determine Foodborne Microbial Toxins","authors":"O. Singh, N. Nagaraj, P. Gabani","doi":"10.1002/9780470744307.GAT229","DOIUrl":"https://doi.org/10.1002/9780470744307.GAT229","url":null,"abstract":"The possible origins of microbial toxins vary widely, and detection of these toxins in different food matrices is a major challenge for food industries and regulatory agencies. New methodologies are needed to quickly and precisely detect traces of micro-organisms and their toxic metabolites. In post-genomics era, systems biology approaches, ranging from genomic sequencing to transcriptomics, proteomics and metabolomic profiling, may be an effective platform for developing tests to identify a variety of toxins in field applications; multiple functional ‘-omics’ could be combined into a system-wide approach for detecting toxins, which may also be useful in the study of microbial pathogenesis. Advances in systems biology are addressed in the current article, as well as possible uses of these high-throughput platforms to ensure food and feed safety.Keywords:genomics;metabolomics;microbial toxins;proteomics;reactome;systems biology;transcriptomics","PeriodicalId":325382,"journal":{"name":"General, Applied and Systems Toxicology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2011-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126787577","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Chemoinformatics and its Applications","authors":"V. Umashankar, S. Gurunathan","doi":"10.1002/9780470744307.GAT222","DOIUrl":"https://doi.org/10.1002/9780470744307.GAT222","url":null,"abstract":"Cheminformatics is the use of computer and informational techniques, applied to a range of problems in the field of chemistry. It is also known as chemoinformatics and chemical informatics. These in silico techniques are used in pharmaceutical companies in the process of drug discovery. Cheminformatics can also be applied to data analysis for various industries such as paper and pulp, dyes and such allied industries. The primary application of cheminformatics is in the storage of information relating to compounds. Quantitative structure–activity relationship (QSAR) analysis also forms a part of cheminformatics. Several in silico cheminformatic tools are currently available for predicting physio-chemical properties and biological activity of many different chemical molecules. Thus, chemoinformatics helps to reduce the time taken for identifying potential drug targets as well as to understand physical, chemical and biological properties of several chemical compounds. Outputs of chemoinformatics may also direct the course of wet laboratory experiments. \u0000 \u0000 \u0000Keywords: \u0000 \u0000cheminformatics; \u0000chemical informatics; \u0000QSAR; \u0000drug design","PeriodicalId":325382,"journal":{"name":"General, Applied and Systems Toxicology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2011-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114970073","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Immunotoxicogenomics: A Systems Approach","authors":"R. Vandebriel, H. Loveren, K. Baken, J. Pennings","doi":"10.1002/9780470744307.GAT228","DOIUrl":"https://doi.org/10.1002/9780470744307.GAT228","url":null,"abstract":"Immunotoxicity can be defined as the adverse effects of toxicants on the immune system. Low-molecular-weight chemicals that are able to induce allergy can be divided into contact and respiratory sensitizers. These sensitizers differ not only in their relevant exposure routes and the clinical effects they can induce, but also in risk assessment. Various types of data suggest that the oxidative stress response pathway is the most significant one affected by contact sensitizer exposure. Less abundant, primarily toxicogenomics, data suggest that the PTEN pathway is the most significant pathway affected by respiratory sensitizer exposure. The chemical characteristics that determine whether a sensitizer is a contact or respiratory sensitizer are beginning to be understood. We hypothesize how the oxidative stress and PTEN pathways may result in the in vivo observations of preferential Th1 and Th2 responses by contact and respiratory sensitizers, respectively. While for contact sensitization risk assessment seems to be feasible, this prospect is still remote for respiratory sensitization, partly because a validated in vivo model and quantitative data are lacking. To be able to identify respiratory sensitizers, we propose to develop non-animal assays on the basis of human data. This proposition also holds for risk assessment of respiratory sensitization. We anticipate that development of non-animal assays as well as risk assessment will depend on a systems toxicology framework. \u0000 \u0000 \u0000Keywords: \u0000 \u0000Keap1; \u0000Nrf2; \u0000PTEN; \u0000respiratory tract; \u0000risk assessment; \u0000toxicogenomics; \u0000sensitizer; \u0000skin; \u0000oxidative stress","PeriodicalId":325382,"journal":{"name":"General, Applied and Systems Toxicology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2011-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122737933","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Biomarker Discovery: Introduction to Statistical Learning and Integrative Bioinformatics Approaches","authors":"D. Repsilber, M. Jacobsen","doi":"10.1002/9780470744307.GAT223","DOIUrl":"https://doi.org/10.1002/9780470744307.GAT223","url":null,"abstract":"In toxicology, biomarkers are needed for use in screenings, time series and dilution series exposure studies for safety evaluation and risk assessment. They need to be easily and reproducibly measurable, and are therefore sought amongst molecular features using OMICs high-throughput technologies in assays of blood and other easily accessible tissue. This chapter conveys methods for screening OMICs datasets for candidate biomarkers for classification. We begin focussing on single biomarker detection, and survey improvements to the t-test as well as multiplicity corrections regarding this objective. Biomarker panels (biosignatures) are patterns of several combined single features. We describe their detection using three different methods of statistical learning. Here, a special focus is on avoiding overfitting through appropriate use of cross-validation. More sophisticated approaches using gene-set enrichment algorithms and steps towards integrated bioinformatics analyses are explained. Making use of a priori knowledge about regulatory structures (gene groups, correlation structures) may further improve classification efficiency of the detected biosignatures. As the red line, we exemplify analysis possibilities using the famous Golub gene expression dataset and the appropriate R-scripts – enabling the reader to reproduce every step on his own desktop. \u0000 \u0000 \u0000Keywords: \u0000 \u0000biomarker; \u0000feature selection; \u0000multivariate signature; \u0000cross-validation; \u0000diagnosis; \u0000prediction; \u0000statistical learning; \u0000integrative bioinformatics","PeriodicalId":325382,"journal":{"name":"General, Applied and Systems Toxicology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2011-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127415642","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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